Artificial Intelligence-Based Mobile Robots: Development Trends and Challenges
TL;DR
This study critically examines the integration of nature-inspired optimization algorithms and deep learning techniques in autonomous mobile robotics, addressing key research gaps related to adaptability, real-time decision-making, and energy-efficient operations.
Abstract
The integration of artificial intelligence (AI) with mobile robotics is transforming automation technologies, enabling advancements across industries such as manufacturing, healthcare, and hazardous material handling. As AI-driven mobile robots become increasingly prevalent, their ability to enhance operational efficiency and safety underscores the need for a comprehensive understanding of their underlying methodologies. This study critically examines the integration of nature-inspired optimization algorithms and deep learning techniques in autonomous mobile robotics, addressing key research gaps related to adaptability, real-time decision-making, and energy-efficient operations. A significant contribution of this work is the exploration of the synergistic application of bio-inspired heuristics and AI-driven perception systems, which substantially improve environmental awareness and autonomous navigation. Furthermore, this review highlights existing limitations in computational complexity and ethical considerations within current frameworks, proposing a structured approach to mitigate these challenges. By systematically analyzing recent advancements and outlining future research directions, this study provides valuable insights that contribute to the development of more robust, intelligent, and ethically responsible autonomous robotic systems.